See the vignette which is included with the qgcomp R package, and is accessible in R via vignette("qgcomp-vignette", package="qgcomp") Read the original paper: Keil et al. A quantile-based g-computation approach to addressing the effects of exposure mixtures. Env Health Persp. 2019; 128...
:exclamation: This is a read-only mirror of the CRAN R package repository. qgcomp — Quantile G-Computation. Homepage: https://github.com/alexpkeil1/qgcomp/ Report bugs for this package: https://github.com/alexpkeil1/qgcomp/issues - cran/qgcomp
qreg — Quantile regression 11 Robust regression attempts to correct the outlier-sensitivity deficiency in ordinary regression: . rreg y x, genwt(wt) Huber iteration 1: Huber iteration 2: Huber iteration 3: Biweight iteration 4: Biweight iteration 5: Biweight iteration 6: Biweight iteration 7...
Computation of the quantile values only for one test statistic.P. Lafaye de MicheauxV. A. Tran
To simplify computation through jackknifing, the Jackknife Empirical Likelihood (JEL) method was proposed by Jing et al. (2009). For statistical inference associated with θ0, inspired by the EL method, Zhou and Jing (2003b) suggested a smoothed empirical likelihood methodology, effectively ...
, we recommend checking out sparklyr.ai, spark.rstudio.com, and also some previous sparklyr release posts such as sparklyr 1.5 and sparklyr 1.4.That is all. Thanks for reading!Greenwald, Michael, and Sanjeev Khanna. 2001. “Space-Efficient Online Computation of Quantile Summar...
QuR. In the relative abundance scale (by Aitchison or GUniFrac dissimilarities), ConQuR also successfully aligned the different batches. However, its advantage over the others was not as substantial as in the raw count scale. This is because ConQuR-libsize and the competing methods either ...
The iteration log is displayed by default unless you used set iterlog off to suppress it; see set iterlog in [R] set iter. verbose displays a verbose log showing the iterations of each computation step. For the IQR estimator, each line is shown for each grid point. For the SEE ...
分位数问题其实就是 quantile(r)问题,即给定 r,根据估计出来的 quantile 函数求出 q'。 函数的误差由多种途径带来: 海量数据必然导致我们需要对数据进行有条件的整合和过滤,由此引入误差。但合理的整合、过滤机制能够将误差控制在一定范围内。为此,无数 researcher 贡献了各种 idea,这也是文档后半部分介绍的主要内...
Family Functions for Quantile Regression " F d P I c C b 0 X 2 P E ) C 0 A 6 D 5 Y 0 X ( W V 9 V U 4 R I HC G t u B s Y g W r q p 4 h x w v t B u s Y g W r q p i h W g f f m d j i G h gf e d h ko d p q w ...